{"id":"https://openalex.org/W4296268977","doi":"https://doi.org/10.3390/rs14184657","title":"3D Sea Surface Electromagnetic Scattering Prediction Model Based on IPSO-SVR","display_name":"3D Sea Surface Electromagnetic Scattering Prediction Model Based on IPSO-SVR","publication_year":2022,"publication_date":"2022-09-18","ids":{"openalex":"https://openalex.org/W4296268977","doi":"https://doi.org/10.3390/rs14184657"},"language":"en","primary_location":{"id":"doi:10.3390/rs14184657","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14184657","pdf_url":"https://www.mdpi.com/2072-4292/14/18/4657/pdf?version=1663668431","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/18/4657/pdf?version=1663668431","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079142451","display_name":"Chunlei Dong","orcid":"https://orcid.org/0000-0002-5815-7962"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunlei Dong","raw_affiliation_strings":["School of Physics, Xidian University, Xi\u2019an 710071, China","School of Physics, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"School of Physics, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Physics, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034046392","display_name":"Xiao Meng","orcid":"https://orcid.org/0000-0002-4410-2995"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Meng","raw_affiliation_strings":["School of Physics, Xidian University, Xi\u2019an 710071, China","School of Physics, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"School of Physics, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Physics, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009314993","display_name":"Lixin Guo","orcid":"https://orcid.org/0000-0003-3854-206X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Guo","raw_affiliation_strings":["School of Physics, Xidian University, Xi\u2019an 710071, China","School of Physics, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"School of Physics, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Physics, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101920826","display_name":"Jiamin Hu","orcid":"https://orcid.org/0000-0002-1413-5737"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiamin Hu","raw_affiliation_strings":["School of Physics, Xidian University, Xi\u2019an 710071, China","School of Physics, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"School of Physics, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Physics, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079142451"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.5672,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.8131508,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"14","issue":"18","first_page":"4657","last_page":"4657"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11061","display_name":"Ocean Waves and Remote Sensing","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10647","display_name":"Coastal and Marine Dynamics","score":0.9731000065803528,"subfield":{"id":"https://openalex.org/subfields/1904","display_name":"Earth-Surface Processes"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.8564352989196777},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.7738375067710876},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7047565579414368},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.5761591196060181},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4782751500606537},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.45094916224479675},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4422285556793213},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3692229092121124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2887744903564453},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18643373250961304},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14608582854270935}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.8564352989196777},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7738375067710876},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7047565579414368},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.5761591196060181},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4782751500606537},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.45094916224479675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4422285556793213},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3692229092121124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2887744903564453},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18643373250961304},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14608582854270935}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14184657","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14184657","pdf_url":"https://www.mdpi.com/2072-4292/14/18/4657/pdf?version=1663668431","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4a860341ced34c2d819f935c49e385f5","is_oa":true,"landing_page_url":"https://doaj.org/article/4a860341ced34c2d819f935c49e385f5","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 18, p 4657 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/18/4657/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14184657","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 18; Pages: 4657","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14184657","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14184657","pdf_url":"https://www.mdpi.com/2072-4292/14/18/4657/pdf?version=1663668431","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.8100000023841858,"display_name":"Life below water"}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3085993365","display_name":null,"funder_award_id":"(Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3748351804","display_name":null,"funder_award_id":"6187145","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G37568934","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4233398540","display_name":null,"funder_award_id":"U20B2059","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5249178904","display_name":null,"funder_award_id":"Grant No. 6","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5381984581","display_name":null,"funder_award_id":"61871457","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G542409138","display_name":null,"funder_award_id":"U21A20457","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5570204100","display_name":null,"funder_award_id":"U21A204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7395238924","display_name":null,"funder_award_id":"U21A2045","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296268977.pdf","grobid_xml":"https://content.openalex.org/works/W4296268977.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1990001693","https://openalex.org/W2016541210","https://openalex.org/W2055429745","https://openalex.org/W2062905974","https://openalex.org/W2080337061","https://openalex.org/W2105572471","https://openalex.org/W2114664437","https://openalex.org/W2149609057","https://openalex.org/W2156909104","https://openalex.org/W2282752563","https://openalex.org/W2340896621","https://openalex.org/W2433989982","https://openalex.org/W2503702045","https://openalex.org/W2546225555","https://openalex.org/W2568426016","https://openalex.org/W2592365852","https://openalex.org/W2767795786","https://openalex.org/W2768782040","https://openalex.org/W2780539948","https://openalex.org/W2781337699","https://openalex.org/W2790354721","https://openalex.org/W2795314092","https://openalex.org/W2809225807","https://openalex.org/W2895847953","https://openalex.org/W2903351561","https://openalex.org/W2913222807","https://openalex.org/W2928253772","https://openalex.org/W2954424132","https://openalex.org/W2955624945","https://openalex.org/W3000009168","https://openalex.org/W3082896320","https://openalex.org/W4205129187","https://openalex.org/W4213288813","https://openalex.org/W4283258785","https://openalex.org/W6695297787"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2102148524","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W2113981829","https://openalex.org/W4382982879","https://openalex.org/W2013466861","https://openalex.org/W4311044000"],"abstract_inverted_index":{"An":[0],"Improved":[1],"Particle":[2,103],"Swarm":[3,104],"Optimization":[4,105],"Algorithm-Support":[5],"Vector":[6],"Regression":[7],"Machine":[8],"(IPSO-SVR)":[9],"prediction":[10,128,135,155,172,180,192,208,225,240,249,255,263,271,290],"model":[11,40,156,209,241,250,272,291],"is":[12,46,61,82,98,114,144,157,182,194,210,227,273,284],"developed":[13],"in":[14,33,292,298,307],"this":[15,293],"paper":[16,294],"to":[17,116,124,212],"predict":[18],"the":[19,25,37,42,50,57,66,70,72,88,102,118,122,131,133,140,153,163,171,175,188,202,206,216,221,233,238,247,254,259,266,278,281,289,299],"electromagnetic":[20],"(EM)":[21],"scattering":[22,39,305],"coefficients":[23,77,138,165,306],"of":[24,41,59,75,139,152,174,187,205,220,237,269,302],"three-dimensional":[26],"(3D)":[27],"sea":[28,44,80,142,303],"surface":[29,45,81,143,304],"for":[30,84,136],"large":[31,308],"scenes":[32],"real-time.":[34],"At":[35],"first,":[36],"EM":[38],"3D":[43,79,141],"established":[47],"based":[48],"on":[49],"Semi-Deterministic":[51],"Facet":[52],"Scattering":[53],"Model":[54],"(SDFSM),":[55],"and":[56,107,120,162,178,190,197,223,229,261,280],"validity":[58],"SDFSM":[60],"verified":[62],"by":[63,100],"comparing":[64],"with":[65,258,277],"measured":[67],"data.":[68],"Using":[69],"SDFSM,":[71,279],"data":[73],"set":[74],"backscattering":[76,137],"from":[78],"generated":[83],"different":[85],"polarizations":[86],"as":[87],"training":[89],"samples.":[90],"Secondly,":[91],"an":[92],"improved":[93],"particle":[94],"swarm":[95],"optimization":[96],"algorithm":[97,113],"proposed":[99],"combining":[101],"(PSO)":[106],"Genetic":[108],"Algorithm":[109],"(GA).":[110],"The":[111,146,184],"combined":[112],"utilized":[115],"optimize":[117],"parameters":[119],"train":[121],"SVR":[123],"build":[125],"a":[126],"regression":[127],"model.":[129],"In":[130],"end,":[132],"extrapolated":[134],"performed.":[145],"Root":[147],"Mean":[148],"Square":[149],"Error":[150],"(RMSE)":[151],"IPSO-SVR-based":[154,179,207,239,248,270],"less":[158],"than":[159,168,286],"1.2":[160],"dB,":[161,199],"correlation":[164,218,235],"are":[166],"higher":[167],"91%.":[169],"And":[170],"accuracy":[173,256],"PSO-SVR-based,":[176],"GA-SVR-based":[177,191,224,262],"models":[181,193,226],"compared.":[183],"average":[185,203,217,234],"RMSE":[186,204],"PSO-SVR-based":[189,222,260],"1.4241":[195],"dB":[196],"1.6289":[198],"respectively.":[200,231],"While":[201,232],"reduced":[211],"1.1006":[213],"dB.":[214],"Besides,":[215],"coefficient":[219,236],"94.36%":[228],"93.93%,":[230],"reached":[242],"95.12%.":[243],"It":[244],"demonstrated":[245],"that":[246],"can":[251],"effectively":[252],"improve":[253],"compared":[257,276],"models.":[264],"Moreover,":[265],"simulation":[267],"time":[268],"significantly":[274],"decreased":[275],"speedup":[282],"ratio":[283],"greater":[285],"15.0.":[287],"Therefore,":[288],"has":[295],"practical":[296],"application":[297],"real-time":[300],"computation":[301],"scenes.":[309]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}
